I could talk hunting and fishing for hours, so I’ll keep this short and sweet.
First, I owe my passion for the outdoors all to my dad. People are the product of the environment they grow up in, right? Well, I pretty much grew up in a boat. Then when I was old enough (like 10 years old), I was sitting in tree stands watching my dad whitetail hunt. I wanted to be just like him, and that’s exactly what I did!
I spend the majority of every summer in Day County South Dakota exploring sloughs for that 30” walleye I have yet to catch. I think I fished at least 5 days a week last summer. How have I not landed a 30” yet?! Every winter I look forward to sight-fishing bluegills in Iowa and catching jumbo perch in South Dakota.
The fall is jam-packed with memories and is clearly my favorite season of the year. My dad and I spend every weekend out West antelope and mule deer hunting in either South Dakota or Wyoming (or both). These hunting trips have given me some amazing experiences but also I’ve sat on a cactus every trip so far so there are some “bad” experiences ;) Let’s not forget about the Iowa whitetail rut in November. Hoooollyyy cow now that is an adrenaline rush! I live for that.
During the week when I’m supposed to be going to school, I go waterfowl hunting with college friends. After everyone is done bickering about how the spread should be set up, the fun begins! The best part is watching the birds work the spread and the dog’s enthusiasm to retrieve. I recently got a new puppy so I’ll be spending even more time in the field, if that’s at all possible.
My newest endeavor is black bear hunting! Late May I will be headed out West to create yet another hunting experience with, you guessed it, my dad! This is completely new for both of us, so this is about to get real interesting.
But let’s be honest, its not all about the harvest. The best part of all of this is spending time with family and friends and providing a way to escape from reality. It is important to pass on this passion to future generations so this sport will never be forgotten. I hope to pay it forward so future generations can make memories in the outdoors with their families, just as I have. Ultimately, my dad has taught me the most important lesson: pursue what makes you happy, and the great outdoors makes me happy.
- Carlee Fletcher
Comments
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https://github.com/fsprojects/FAKE/issues/2861
https://github.com/voidint/g/issues/152
https://github.com/ImkeF/M/issues/12
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https://github.com/dmpe/R/issues/16
https://github.com/adamdruppe/arsd/issues/482
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https://github.com/udlbook/udlbook/issues/275
https://github.com/selfteaching/the-craft-of-selfteaching/issues/1204
https://github.com/LeeJunHyun/Image_Segmentation/issues/99
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https://www.bitsdujour.com/profiles/ffPEOy
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https://github.com/8DIAMOND168/Mack/issues/1
https://github.com/7DIAMOND168/Mack1/issues/1
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Virtualization
Report of the research group “Oflameron”
Topic:
“Ways of virtualization of consciousness”
Brief machine translation.
Decoding the human genome made it possible to begin machine (computer) analysis of the structure, connections and interactions of its elements. The expansion of available computing resources made it possible to analyze the properties of various spatial structures using neural networks.
The achieved level of research does not currently allow for a complete modeling of the work of proteins in a single cell. However, it is now possible to begin developing algorithms and software for modeling and neural networks to assess the quality of modeling (by coincidences with the functioning of a real cell) – stage 1. As available computing power grows, it will be possible to begin modeling the activity of a single living cell with training of a neural network (networks). This will be the FIRST stage of virtualization of a living unicellular organism. After achieving high accuracy of coincidence between the virtual model and the real organism, you can proceed to the next stage.
At the next stage (2), you can model the “fertilization process” and cell division. That is, the modeling will move to the level of a simple multicellular organism. At this stage, a high degree of coincidence with a real organism (embryo) should be achieved. The reactions to any impacts and the sequence of the development process should coincide. This can be achieved provided that the control neural networks are appropriately improved and trained. At the moment, there is insufficient computing power for this, but such resources (estimated) should appear within 15-25 years.
The next horizon is stage 3. At this stage, the transition will not only be made to a multicellular virtual organism, but a virtual nervous system with a high degree of coincidence with the real model (living organism) should also be “formed”. This is the most important qualitative transition, from which the period of consciousness virtualization essentially begins.
At stage 4, it is necessary to achieve modeling of the thinking process. This will be the first stage of virtual consciousness modeling. The corresponding control neural networks at this stage will differ greatly from the original networks of stages 1-2. And they will have parameters and accumulated coefficients that can be interpreted only by special programs (special neural networks). A very rough estimate of the time period is 50-70 years from the start of the work.
Stage 5 will be associated with the independent development of the virtual organism and neural networks (to assess the accuracy of modeling and interpretation of results). Interpretation of the results is needed to achieve the set goals:
- achieving complete coincidence of the virtual model with the real organism
- defining the mechanism of identification of the individual (consciousness)
- developing a mechanism for transmitting the individual
- preventing situations of “uncontrolled independence”
…
This report is the first document that outlines the main stages of work in the process of virtualization of human consciousness. This approach to precise virtual modeling (virtual development, virtual life) is fundamentally different from the current work on Artificial Intelligence (the “top-down” approach, without understanding the internal mechanism of consciousness). It will give the maximum achievable result.
This document allows using real data as input – graphs and forecasts of growth in the performance of computing systems and thereby more accurately predicting the times of passing the corresponding stages.
© by Oflameron Group
Rarely used dataset for training Artificial Intelligence – linguistic “board games on paper”. https://geocities.ws/frenchfree/ Such datasets are easily converted into electronic form (.TXT, .PDF or .DOCX files) and can generate millions of values for new datasets (scale).